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Quantum error correction (QEC) is a cornerstone of quantum computing, enabling reliable information processing in the presence of noise. Sparse stabilizer codes -- referred to generally as quantum low-density parity-check (QLDPC) codes --…

Quantum Physics · Physics 2025-10-20 Bane Vasic , Valentin Savin , Michele Pacenti , Shantom Borah , Nithin Raveendran

Achieving high image quality is an important aspect in an increasing number of wireless multimedia applications. These applications require resource efficient error correction hardware to detect and correct errors introduced by the…

Information Theory · Computer Science 2013-08-02 Vikram Arkalgud Chandrasetty , Syed Mahfuzul Aziz

While linear programming (LP) decoding provides more flexibility for finite-length performance analysis than iterative message-passing (IMP) decoding, it is computationally more complex to implement in its original form, due to both the…

Information Theory · Computer Science 2009-02-05 Mohammad H. Taghavi , Amin Shokrollahi , Paul H. Siegel

In this paper, we deal with the problem of jointly determining the optimal coding strategy and the scheduling decisions when receivers obtain layered data from multiple servers. The layered data is encoded by means of Prioritized Random…

Information Theory · Computer Science 2016-11-18 Nikolaos Thomos , Eymen Kurdoglu , Pascal Frossard , Mihaela Van der Schaar

In this paper we propose the construction of Spatially Coupled Low-Density Parity-Check (SC-LDPC) codes using a periodic time-variant Quasi-Cyclic (QC) algorithm. The QC based approach is optimized to obtain memory efficiency in storing the…

Information Theory · Computer Science 2013-10-18 Vikram Arkalgud Chandrasetty , Sarah J. Johnson , Gottfried Lechner

Research on polar codes has been constantly gaining attention over the last decade, by academia and industry alike, thanks to their capacity-achieving error-correction performance and low-complexity decoding algorithms. Recently, they have…

Information Theory · Computer Science 2020-06-25 Carlo Condo , Valerio Bioglio , Ingmar Land

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant…

Machine Learning · Computer Science 2023-09-26 Giorgos Bouritsas , Andreas Loukas , Nikolaos Karalias , Michael M. Bronstein

Designing a practical, low complexity, close to optimal, channel decoder for powerful algebraic codes with short to moderate block length is an open research problem. Recently it has been shown that a feed-forward neural network…

Information Theory · Computer Science 2017-02-27 Eliya Nachmani , Elad Marciano , David Burshtein , Yair Be'ery

This paper presents several new construction techniques for low-density parity-check (LDPC) and systematic repeat-accumulate (RA) codes. Based on specific classes of combinatorial designs, the improved code design focuses on high-rate…

Information Theory · Computer Science 2018-07-03 Alexander Gruner , Michael Huber

In Linear Programming (LP) decoding of a Low-Density-Parity-Check (LDPC) code one minimizes a linear functional, with coefficients related to log-likelihood ratios, over a relaxation of the polytope spanned by the codewords \cite{03FWK}. In…

Information Theory · Computer Science 2007-07-13 Michael Chertkov , Mikhail G. Stepanov

We consider transmission over a binary-input additive white Gaussian noise channel using low-density parity-check codes. One of the most popular techniques for decoding low-density parity-check codes is the linear programming decoder. In…

Information Theory · Computer Science 2015-03-19 Shrinivas Kudekar , Jason K. Johnson , Misha Chertkov

In streaming applications, doping improves the performance of spatially-coupled low-density parity-check (SC-LDPC) codes by creating reduced-degree check nodes in the coupled chain. We formulate a scaling law to predict the bit and block…

Information Theory · Computer Science 2021-04-23 Roman Sokolovskii , Alexandre Graell i Amat , Fredrik Brännström

In this paper, we present an efficient algorithm to sample random sparse matrices to be used as check matrices for quantum Low-Density Parity-Check (LDPC) codes. To ease the treatment, we mainly describe our algorithm as a technique to…

Information Theory · Computer Science 2026-01-27 Paolo Santini

Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. LP decoding has been derived for binary and nonbinary linear codes. However, the most…

Information Theory · Computer Science 2016-11-17 Mayur Punekar , Pascal O. Vontobel , Mark F. Flanagan

CC-GLPDC codes are a class of generalized low-density parity-check (GLDPC) codes where the constraint nodes (CNs) represent convolutional codes. This allows for efficient decoding in the trellis with the forward-backward algorithm, and the…

Information Theory · Computer Science 2022-12-01 Muhammad Umar Farooq , Michael Lentmaier , Alexandre Graell i Amat

The use of deep learning-based techniques for approximating secure encoding functions has attracted considerable interest in wireless communications due to impressive results obtained for general coding and decoding tasks for wireless…

Information Theory · Computer Science 2021-06-02 Rick Fritschek , Rafael F. Schaefer , Gerhard Wunder

Spatially coupled low-density parity-check (SC-LDPC) codes can achieve the channel capacity under low-complexity belief propagation (BP) decoding, however, there is a non-negligible rate-loss because of termination effects for practical…

Information Theory · Computer Science 2015-12-16 Sebastian Cammerer , Vahid Aref , Laurent Schmalen , Stephan ten Brink

Most existing works on analyzing the performance of a random ensemble of low-density parity-check (LDPC) codes assume that the degree distributions of the two ends of a randomly selected edge are independent. In the paper, we take one step…

Information Theory · Computer Science 2023-04-20 Hsiao-Wen Yu , Cheng-En Lee , Ruhui Zhang , Cheng-Shang Chang , Duan-Shin Lee

Although iterative decoding of polar codes has recently made huge progress based on the idea of permuted factor graphs, it still suffers from a non-negligible performance degradation when compared to state-of-the-art CRC-aided successive…

Information Theory · Computer Science 2020-01-20 Marvin Geiselhart , Ahmed Elkelesh , Moustafa Ebada , Sebastian Cammerer , Stephan ten Brink

Successive-cancellation list (SCL) decoding of polar codes has been adopted for 5G. However, the performance is not very satisfactory with moderate code length. Heuristic or deep-learning-aided (DL-aided) flip algorithms have been developed…

Information Theory · Computer Science 2021-06-25 Yaoyu Tao , Zhengya Zhang
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